| Zugriffsnummer | 51333 |
| Dokumenttyp | Zeitschriftenartikel |
| Peer Review | mit Peer Review |
| Sprache | Englisch |
| Titel | Compressed AFM-IR hyperspectral nanoimaging |
| Autor(in); Institution |
Hornemann, Andrea; 7.1, Radiometrie mit Synchrotronstrahlung, PTB-Berlin
Metzner, Selma; 8.1, Biomedizinische Magnetresonanz, PTB-Berlin
Patoka, Piotr; Physikalische Chemie, Freie Universität Berlin, Berlin, GERMANY
Cortes, S.; Global Health and Tropical Medicine (GHTM), Instituto de Higiene e Medicina Tropical (IHMT), Universidade NOVA de Lisboa, Lisbon, PORTUGAL
Rühl, Eckart; Physikalische Chemie, Freie Universität Berlin, Berlin, GERMANY
Elster, Clemens; 8.4, Mathematische Modellierung und Datenanalyse, PTB-Berlin
|
| Quelle/Jahr | Measurement Science and Technology: 35 (2023), 1 - 8 |
| Artikelnummer | 015403 |
| ISSN | 0957-0233 (print) ; 1361-6501 (online) |
| DOI | |
| Verlag | Bristol: IOP Publishing |
| Freie Schlagworte | AFM-IR ; hyperspectral nanoimaging ; low-rank matrix reconstruction ; Leishmania parasites |
| Zusammenfassung | Infrared (IR) hyperspectral imaging is a powerful approach in the field of materials and life sciences. However, for the extension to modern sub-diffraction nanoimaging it still remains a highly inefficient technique, as it acquires data via inherent sequential schemes. Here, we introduce the mathematical technique of low-rank matrix reconstruction to the sub-diffraction scheme of atomic force microscopy-based infrared spectroscopy (AFM-IR), for efficient hyperspectral IR nanoimaging. To demonstrate its application potential, we chose the trypanosomatid unicellular parasites Leishmania species as a realistic target of biological importance. The mid-IR spectral fingerprint window covering the spectral range from 1300 to 1900 cm-1 was chosen and a distance between the data points of 220 nm was used for nanoimaging of single parasites. The method of k-means cluster analysis was used for extracting the chemically distinct spatial locations. Subsequently, we randomly selected only 10% of an originally gathered data cube of 134 (x) x 50 (y) x 148 (spectral) AFM-IR measurements and completed the full data set by low-rank matrix reconstruction. This approach shows agreement in the cluster regions between full and reconstructed data cubes. Furthermore, we show that the results of the low-rank reconstruction are superior compared to alternative interpolation techniques in terms of error-metrics, cluster quality, and spectral interpretation for various subsampling ratios. We conclude that by using low-rank matrix reconstruction the data acquisition time can be reduced from more than 14 h to 1-2 h. These findings can significantly boost the practical applicability of hyperspectral nanoimaging in both academic and industrial settings involving nano- and bio-materials. |
| Kostenfreier Zugang | Open Access Hybrid |
| Rechteinformation | CC BY 4.0 ; Creative Commons Attribution 4.0 License |
| Themenbereich der Metrologie | Photometrie und Radiometrie |